Iain Carmichael and Michael Kim recently gave a presentation at the PyData Carolinas conference on the topic of Networks and the Law. For their talk they analyzed data from CourtListener, applying a variety of network algorithms to identify important or influential cases.

Abstract

What does network science have to say about the law? Can we determine which are the most the most influential cases in our legal system? Can we understand how legal doctrine evolves? Using tools from network statistics and data provided by Court Listener (an open legal data project), we analyze the network of law case citations.

Citation networks have recently been a topic of interest to network scientists. Court Listener, an open data initiative, provides the network of law case citations as well as the text of (almost every) court case in the US. This network data set provides a rich array of questions that are of interest to legal scholars as well as network scientists.

Can we determine which cases are the most influential in our legal system? Can we understand how legal doctrine evolves? We will discuss what we learned about how the network of law cases evolves and what this means for legal practitioners.